Computational modelling of NOx removal by selective non-catalytic reduction

This paper presents the results of computational kinetic modelling of the removal of nitrogen oxides (NO_x) from flue gases by selective non-catalytic reduction (SNCR) process using urea as a reducing agent. CHEMKIN and SENKIN computer codes were used with latest reaction mechanism parameters for simulated conditions in an isothermal plug flow reactor. Flue gas initial conditions were simulated as 70 litres/min propane containing 500 ppm background NO_x. A range of molar ratios was studied at optimum temperature. Carbon monoxide and hydrogen were investigated as potential enhancers to lower the temperature window. The modelling results suggested that the optimum temperature for peak reduction was around 1075°C with optimum molar ratios of 1.5. Hydrogen was found to be an efficient enhancer. The optimum residence time was found to be about 80 milliseconds.     

Short-term prediction of means of artificial neural urban NO2 pollution by networks

A neural network model for the short-term prediction of concentrations of urban pollutants was developed and applied to the Turin (Northern Italy) air quality network. In particular, the study was focused on NO₂ concentrations measured at five stations; t + 3 and t + 24 hour NO₂ concentration forecasting based on hourly meteorological and concentration data gave good agreement with observed concentrations. This is particularly true for the mean concentration values and concentration distribution. The time of occurrence of peak values was correctly forecast but the amounts were generally underestimated. To reduce this underestimation, an empirical step function was applied in the t + 24 case. This allowed an accurate estimate to be obtained of the few cases in which 50% of the air quality monitoring stations exceeded the attention level (200 μg m^-3) during the following day for at least one hour.     

Changing consumption patterns and CO2 reduction

Today, most countries are facing national CO₂ targets focused on production and direct energy use. However, two important driving forces are increased consumption and changing consumption patterns. In this paper, we analyse the impact from household consumption on CO₂ emissions. Household energy use is taken into account, as is the consumption of commodities and services produced by industry. Based on Danish data, we estimate the CO₂ impact from different commodities. Further, we analyse the impact of changes in commodity mix in Danish household consumption in the period from 1966 to 1992. The results show that the change in commodity mix has been insufficient to compensate for the overall growth in Danish consumption. Further, we see that the consumption of food is a main contributor to overall Danish CO₂ emissions.     

Source contribution of atmospheric aerosols in Bangkok metropolitan area by CMB8 receptor model

The CMB₈ model was applied for source apportionment of particulate matter in Bangkok area. The 24 h of ambient data were collected and analysed for elemental composition during December 1996 to January 1997 by high volume air samplers at a station in Bangkok, Thailand. Seven source profiles and the average mass concentrations of 42 ambient data were used to run the chemical mass balance (CMB₈) model. The source apportionment by CMB₈ gave similar results comparing with factor analysis – multiple regression (FA–MR) model of the same data. The results revealed that major sources of particulate matter in Bangkok were: soil (33%), road dust (33%) and automobile (15%). The minor source contributions were: sea salt (4.34%), refuse incineration and biomass burning (0.84%), steel mill (0.62%) and fuel oil combustion (0.35%). The lack of source profile for biomass or open burning in Bangkok resulted in much lower predicted contribution of this source when compared to that from FA–MR. When apply this CMB₈ model with daily ambient data, the result revealed that one fourth of daily CMB₈ source apportionment had high value of ² (>4). These exceedance values of Chi² also point out that one of the selected sources (biomass burning) may not be the true contributing sources. Presumably, accurate biomass burning source profile is needed to improve the CMB calculation of source contributions for particulate matter in Bangkok metropolitan area.     

Analysis and interpretation of the monitoring data for C2–C11 hydrocarbons in the atmosphere of a rural Portuguese site

This paper focuses the application of a measurement technique for determining atmospheric C₂–C₆ hydrocarbons after canister sampling and analysis by gas chromatography/flame ionisation detection (GC/FID), as well of an adsorption-sampling technique for C₆–C₁₁ compounds and GC/FID analysis after thermal desorption and cryogenic concentration. Tens of samples collected at Giesta, a rural area located 20 km to the SE of the coastal Portuguese city of Aveiro, were analysed. The characterisation of C₂ C₁₁ hydrocarbons is presented, considering seasonal variations, diurnal cycles, the influence of air masses and different photochemical conditions. Ratios between hydrocarbons and principal components analysis were applied to differentiate between biogenic and anthropogenic sources.     

The econometric approach to CO2 concentration modelling: uncertainties and the policy dimension

The purpose of this paper is to review from a critical point of view some of the attempts we have made to model CO2 concentrations in the atmosphere in relation to ongoing carbon emissions and their connection with energy use. These results have been published previously in the International Journal of Global Energy Issues and the International Journal of Environment and Pollution and are annexed as Tables 1 and 2.     

Sensitivity analysis of the CERES-wheat model for variations in CO2 and meteorological factors in Northwest Turkey

Plant growth is very sensitive to variations in atmospheric factors. Possible effects of climate change on plant growth can be estimated and evaluated using the crop growth simulation models. In this study, the CERES (Crop Environment Resource Synthesis)-wheat model was applied to two consequent growing seasons (1997–1998 and 1998–1999) in order to determine the model sensitivity on the changes in several meteorological factors such as air temperature, precipitation, solar radiation and carbon dioxide (CO₂) concentration. In the model, the air temperature variations were applied from ±1°C up to ±2°C and CO₂ were changed in the range of 20% to 100%, while the solar radiation, precipitation were varied between 10% and 20%. Biomass and the grain yield of the wheat crop were influenced positively by the increased combination of the solar radiation, air temperature and CO₂. However, low crop responses to the variations in precipitation were unexpected.     

Preparation, characterisation and testing of photocatalytic polymeric membranes with entrapped or suspended TiO2

Various cellulose triacetate (CTA) or polysulfone (PSf) membranes with entrapped polycrystalline TiO₂ were prepared by using different methods of the so-called phase inversion process. Porosity and permeability of the membranes increased by increasing the amount of entrapped TiO₂ while rejection decreased. The photoactivity of entrapped TiO₂ for the degradation of congo-red was compared with that of the same quantity of suspended TiO₂ and the results indicated that TiO₂ was always more efficient when used in suspension. A hybrid configuration consisting of a continuous membrane photoreactor with the photocatalyst in suspension showed to be the most promising one.     

Sustainable urban transportation: impact of CO2 mitigation strategies on local pollutants

This paper assesses CO₂ mitigation strategies in Delhi and Mumbai against the dynamics of local pollutants. After testing against techno-economic feasibility, compressed natural gas (CNG) technology, four-stroke two-wheelers and battery-operated vehicles (BOV) were selected as candidate options for Mumbai and Delhi. Multiple constrained optimisation for finding out the optimal mix of vehicles to meet the travel demand under the business-as-usual scenario for the period of CO₂ mitigation targets of 5, 10, 15, 20, 25% resulted in reduced stock of diesel and petrol vehicles, with the reduction spanning over different points of the above time period. In the case of Mumbai, battery-operated three-wheelers dominated the vehicular mix, with the share of CNG vehicles remaining at a standard level. CO₂ reduction targets did not influence the CNG option significantly. CO₂ mitigation influenced the dynamics of local pollutants considerably in both Delhi and Mumbai. In Delhi, TSP and SOx reduction levels against the CO₂ mitigation target were found to be significant. In Mumbai, the percentage reduction in local pollution (TSP in particular) was higher than the target CO₂ reduction. Local pollutants other than TSP and SO_x showed an increasing trend against the CO₂ mitigation strategies in Delhi. In the case of Mumbai, all non-target pollutants showed a falling trend against the CO₂ mitigation strategies, though insignificantly for pollutants other than TSP and SO_x.     

Modelling emission trends from non-constant time series of PM10 concentrations in Christchurch, New Zealand

This paper presents an attempt to model the trend of emissions through analysis of a time series of PPM₁₀ concentrations in Christchurch, New Zealand. Emissions are not constant over time, but show high seasonality. Fluctuations are removed by creating a time series in which concentrations do not show dependency on ambient air temperature. Remaining meteorological influences are removed through multiple linear regression. Finally, a moving average filter is applied to reveal the low-frequency trend in the residuals of the meteorologically adjusted time series. The modelled trend shows a peak in emissions in 2001-2002 with a steady decrease thereafter.     

Exploratory study of some potential environmental impacts of CO2 sequestration in unmineable coal seams

An initial investigation into the potential environmental impacts of CO₂ sequestration in unmineable coal seams has been conducted, focusing on changes in the produced water during enhanced coalbed methane (ECBM) production, using a CO₂ injection process (CO₂-ECBM). A high volatile bituminous coal, Pittsburgh No. 8, was reacted with synthetic produced water and gaseous carbon dioxide at 40°C and 50 bar to evaluate the potential for mobilisation of toxic metals during CO₂-ECBM/sequestration. Microscopic and X-ray diffraction analysis of the post-reaction coal samples clearly show evidence of chemical reaction and chemical analysis of the synthetic produced water shows substantial changes in composition. These results suggest that changes to the produced water chemistry and the potential for mobilising toxic trace elements from coal beds are important factors to be considered when evaluating deep, unmineable coal seams for CO₂ sequestration.     

The effect of BOD5 and flow-rate of activated sludge systems on investment and energy costs

In this study of wastewater treatment, the effect of flow-rate, BOD₅ and other design parameters (MLSS, mean cell-residence time, etc.) on aeration tank dimensions, investment amount and energy cost has been investigated. The relations among these parameters are represented with mathematical equations, which could be useful in new plant design and in the estimation of investment and energy costs.     

Synthesis of Na-Pc zeolite from perlite and study of its ability to remove cyanide from liquid wastes

With the aim of the economic upgrading of natural resources, this investigation examined the hydrothermal synthesis of zeolite from perlite, and the ability of the synthetic zeolite to adsorb and retain cyanide. The hydrothermal treatment of perlite with aqueous sodium hydroxide results in the formation of Na-P_c zeolite. The cation-exchange capacity of zeolite for zinc, copper and silver was respectively 2.26, 1.86 and 2.44 meq g^-1. The exchange was incomplete, but equilibrium was rapidly attained. Cyanide adsorption isotherms, constructed at three different temperatures, showed that the zeolite was very selective for cyanide. The solubility products of the cyanide precipitate and the exchange capacity of zeolite for individual cations governed the adsorption capacity of the zeolite. The method also remains selective in the presence of some other anions. Kinetic data for cyanide desorption in water and sodium chloride solution indicated that zeolite retains most of the adsorbed cyanide.     

Separate determination of PM10 emission factors of road traffic for tailpipe emissions and emissions from abrasion and resuspension processes

Little is known about the relevance of mechanically produced particles of road traffic from abrasion and resuspension processes in relation to the exhaust pipe particles. In this paper, emission factors of PM₁₀ and PM₁ for light and heavy-duty vehicles were derived for different representative traffic regimes from concentration differences of particles and nitrogen oxides (NO_x) in ambient air upwind and downwind of busy roads, or alternatively of kerbsides and nearby background sites. Hereby, PM₁ was interpreted as direct exhaust emissions and PM₁₀-PM₁ as mechanically produced emissions from abrasion and resuspension processes. The results show that abrasion and resuspension processes represent a significant part of the total primary PM₁₀ emissions of road traffic. At sites with relatively undisturbed traffic flow they are in the same range as the exhaust pipe emissions. At sites with disturbed traffic flow due to traffic lights, emissions from abrasion/resuspension are even higher than those from the exhaust pipes.     

Analytical formulas for the below-cloud scavenging coefficient of an irreversibly soluble gas: a quantitative evaluation for HNO3

In the present paper, analytical expressions are derived for the below-cloud gas scavenging coefficient, considering various functions that can be found in the literature to describe raindrop populations and terminal velocities. Three primary cases have been identified where an analytical solution exists: (i) a raindrop size distribution described by a gamma function and raindrop terminal velocity by a power function of raindrop size; (ii) a raindrop size distribution described by a gamma function and raindrop terminal velocity by an exponential function; and (iii) a raindrop size distribution described by a log–normal function and raindrop terminal velocity by a power function. In addition, in case (i), the gas scavenging coefficient is expressed analytically as a function of rain intensity. The derived analytical expressions are subsequently used to compute the scavenging coefficients of HNO₃ for different parameterizations of the raindrop size distribution and terminal velocity functions. In order to broaden the sensitivity test of HNO3 scavenging coefficients on parameterizations, scavenging coefficients of HNO₃ are also computed numerically for the raindrop terminal velocity as a function of raindrop size and atmospheric conditions. The results show that there is a relative variation in the values of the gas scavenging coefficient up to 50% for the parameterization considered in this study, and that the overestimation given by the analytical formulas is not important for cut-off limits of raindrop spectra below 0.2 mm.     

Limited provision of roads as a bottleneck on vehicle CO2 emissions in Asia: an international comparison of national trends

This paper explores the relationship between road infrastructure, economic growth and road CO₂ emissions. The basic premise is that many developing nations have achieved sufficient wealth to generate substantial demand for road vehicles, but that actual use is constrained by limited provision of surfaced roads. Our main result is that for comparable levels of income (GDP/capita), CO₂ emissions per length of paved road are far higher in rapidly developing Asia as compared to the USA. These findings suggest existence of an 'infrastructure bottleneck', that when relieved, may influence the future trajectory of road transport CO₂ emissions in developing Asia.     

CO2 emission from cement manufacturing and its driving forces in China

This paper addresses two related conceptual and practical challenges in assessing sustainability. The first involves the social context, specifically the criteria and procedures to be used. The second involves the spatial context, specifically the problem of assessing sustainability when there are multiple and overlapping 'communities' with multiple economic and ecological scales. With respect to the first issue, we build on previous contributions in discussing how multicriteria assessment strategies and stakeholder processes might be used. We also illustrate the use of various non-monetary measures of ecological capacity and performance to supplement economic information. The second issue remains less well understood, though our analysis highlights how economic and ecological capacity and performance measures can be applied at various scales.     

Analyses of technical options for mitigating CO2 emissions from an urban transport system: a case study of Beijing City

This paper aims to extrapolate the energy consumption and environmental emissions data on the urban passenger transport system in Beijing, to assess the cost-effectiveness and emission reduction potential of promising technology options for transport systems, and to identify options with both reduction potential and cost-effectiveness. Furthermore, it identifies major barriers to the adoption of such options in Beijing. The long-range Energy Alternatives Planning model, the least-cost approach and the Analytical Hierarchy model are used for these three purposes, respectively. The results show that the fuel demand in the Beijing urban passenger transport system will increase rapidly in the future, along with travel demand and vehicle stock. For CO₂ mitigation targets, diesel vehicles have both emission reduction potential and cost-effectiveness, followed by mass rapid transport systems. The ranking of barriers is similar for all three technology options, and found to be financial incentive, public awareness, lack of infrastructure, high initial cost and institutional/administrative barriers, in descending order of importance. Lack of financial incentive plays a very important role in the adoption of new technology options.     

Assessment of variations in atmospheric PCDD/Fs by Asian dust in Southeastern Korea

Atmospheric concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) were measured in southeastern Korea during the spring of 2002. During this period, severe Asian dust events (ADs) occurred throughout Korea. Total suspended particulates (TSP) of ADs (456.8 μg m⁻³) increased approximately 3.6-fold compared with non-Asian dust events (NADs; 128.5 μg m⁻³). However, the concentrations of PCDD/Fs (average concentration, 3.34 pg m⁻³) did not increase as much as TSP; there was not a significant difference in the concentrations of particle-bound PCDD/Fs collected between ADs (2.45 pg m⁻³) and NADs (2.05 pg m⁻³). Meanwhile, according to TSP levels, the concentrations during NADs were 2.8-fold higher than ADs (16.73 and 5.98 ng g⁻¹-TSP, respectively). High TSP levels during sand storms without an increase in PCDD/Fs reflected an increase in coarse and accumulation mode particles. Gas/particle partitioning studies revealed the additional inputs of particulate matters to the air during ADs which did not relate with the increase of PCDD/Fs. Furthermore, emissions from ADs may consist of relatively complex atmospheric particles; back trajectories showed air masses moving at low altitudes over Korea, but there were no differences in PCDD/Fs or atmospheric pollutants regardless of air movements. The study area, which is located in southeastern Korea, might be affected by both marine and regional anthropogenic sources, which do not appear to cause clear differences in PCDD/F concentrations or congener profiles between different air trajectories.     

A neural network-based approach for the prediction of urban SO2 concentrations in the Istanbul metropolitan area

A three-layer Artificial Neural Network (ANN) model was developed to forecast air pollution levels. The subsequent SO₂ concentration (24-hour averaged) being the output parameter of this study was estimated by seven input parameters such as preceding SO₂ concentrations (24-hour averaged), average daily temperature, sea-level pressure, relative humidity, cloudiness, average daily wind speed and daily dominant wind direction. After Backpropagation training combined with Principal Component Analysis (PCA), the proposed model predicted subsequent SO₂ values based on measured data. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.770, 0.744 and 0.751 for the winter, summer and overall data, respectively.